The LLM Triangle: Engineering Principles for Robust AI Applications - Almog Baku:
Feb 22, 2025 · 26:19
Almog Baku introduces the LLM Triangle Principles for building production-ready AI applications, arguing that LLMs should be treated like interns guided by Standard Operating Procedures (SOPs). He breaks down the triangle into three components: the foundation model, engineering techniques, and contextual data, all directed by SOPs derived from expert interviews. Baku contrasts autonomous agents—creative but unpredictable—with handcrafted LLM-native architectures that offer sustainable quality, recommending scoped autonomy. He advises starting with large models to collect data and optimize incrementally, rather than fine-tuning from day one. Data is paramount: 'show, don't tell' via few-shot examples, and balance context to avoid the 'needles in a haystack' problem. The framework aims to turn demos into robust production systems.
